The temperature-mortality relationship in China: An analysis from 66 Chinese communities

Projecting future minimum mortality temperature in China

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030-2039), 2060 s (2060-2069), and 2090 s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

Random Forest and Feature Importance Measures for Discriminating the Most Influential Environmental Factors in Predicting Cardiovascular and Respiratory Diseases

BACKGROUND

Several studies suggest that environmental and climatic factors are linked to the risk of mortality due to cardiovascular and respiratory diseases; however, it is still unclear which are the most influential ones. This study sheds light on the potentiality of a data-driven statistical approach by providing a case study analysis.

METHODS

Daily admissions to the emergency room for cardiovascular and respiratory diseases are jointly analyzed with daily environmental and climatic parameter values (temperature, atmospheric pressure, relative humidity, carbon monoxide, ozone, particulate matter, and nitrogen dioxide). The Random Forest (RF) model and feature importance measure (FMI) techniques (permutation feature importance (PFI), Shapley Additive exPlanations (SHAP) feature importance, and the derivative-based importance measure (κALE)) are applied for discriminating the role of each environmental and climatic parameter. Data are pre-processed to remove trend and seasonal behavior using the Seasonal Trend Decomposition (STL) method and preliminary analyzed to avoid redundancy of information.

RESULTS

The RF performance is encouraging, being able to predict cardiovascular and respiratory disease admissions with a mean absolute relative error of 0.04 and 0.05 cases per day, respectively. Feature importance measures discriminate parameter behaviors providing importance rankings. Indeed, only three parameters (temperature, atmospheric pressure, and carbon monoxide) were responsible for most of the total prediction accuracy.

CONCLUSIONS

Data-driven and statistical tools, like the feature importance measure, are promising for discriminating the role of environmental and climatic factors in predicting the risk related to cardiovascular and respiratory diseases. Our results reveal the potential of employing these tools in public health policy applications for the development of early warning systems that address health risks associated with climate change, and improving disease prevention strategies.

Evaluating the temperature-mortality relationship over 16 years in Cyprus

In many regions of the world, the relationship between ambient temperature and mortality is well-documented, but little is known about Cyprus, a Mediterranean island country where climate change is progressing faster than the global average. We Examined the association between daily ambient temperature and all-cause mortality risk in Cyprus. We conducted a time-series analysis with quasipoisson distribution and distributed lag non-linear models to investigate the association between temperature and all-cause mortality from 1 January 2004 to 31 December 2019 in five districts in Cyprus. We then performed a meta-analysis to estimate the overall temperature-mortality dose-response relationship in Cyprus. Excess mortality was computed to determine the public health burden caused by extreme temperatures. We did not find evidence of heterogeneity between the five districts (p = 0.47). The pooled results show that for cold effects, comparing the 1st, 2.5th, and 5th percentiles to the optimal temperature (temperature associated with least mortality, 25 ℃), the overall relative risks of mortality were 1.55 (95% CI: 1.32, 1.82), 1.41 (95% CI: 1.21, 1.64), and 1.32 (95% CI: 1.15, 1.52), respectively. For heat effects, the overall relative risks of mortality at the 95th, 97.5th and 99th percentiles were 1.10 (95% CI: 1.04, 1.16), 1.17 (95% CI: 1.07, 1.29), and 1.29 (95% CI: 1.11, 1.5), respectively. The excess mortality attributable to cold days accounted for 8.0 deaths (95% empirical CI: 4.5-10.8) for every 100 deaths, while the excess mortality attributable to heat days accounted for 1.3 deaths (95% empirical CI: 0.7-1.7) for every 100 deaths. The results prompt additional research into environmental risk prevention in this under-studied hot and dry region that could experience disproportionate climate change related exposures.Implications: The quantification of excess mortality attributable to temperature extremes shows an urgent need for targeted public health interventions and climate adaptation strategies in Cyprus and similar regions facing rapid climate change. Future steps should look into subpopulation sensitivity, coping strategies, and adaptive interventions to reduce potential future risks.

Effects of the interaction between cold spells and fine particulate matter on mortality risk in Xining: a case-crossover study at high altitude

Background

With global climate change, the health impacts of cold spells and air pollution caused by PM2.5 are increasingly aggravated, especially in high-altitude areas, which are particularly sensitive. Exploring their interactions is crucial for public health.

Methods

We collected time-series data on meteorology, air pollution, and various causes of death in Xining. This study employed a time-stratified case-crossover design and conditional logistic regression models to explore the association between cold spells, PM2.5 exposure, and various causes of death, and to assess their interaction. We quantitatively analyzed the interaction using the relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). Moreover, we conducted stratified analyses by average altitude, sex, age, and educational level to identify potential vulnerable groups.

Results

We found significant associations between cold spells, PM2.5, and various causes of death, with noticeable effects on respiratory disease mortality and COPD mortality. We identified significant synergistic effects (REOI>0, AP > 0, S > 1) between cold spells and PM2.5 on various causes of death, which generally weakened with a stricter definition of cold spells and longer duration. It was estimated that up to 9.56% of non-accidental deaths could be attributed to concurrent exposure to cold spells and high-level PM2.5. High-altitude areas, males, the older adults, and individuals with lower educational levels were more sensitive. The interaction mainly varied among age groups, indicating significant impacts and a synergistic action that increased mortality risk.

Conclusion

Our study found that in high-altitude areas, exposure to cold spells and PM2.5 significantly increased the mortality risk from specific diseases among the older adults, males, and those with lower educational levels, and there was an interaction between cold spells and PM2.5. The results underscore the importance of reducing these exposures to protect public health.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Identifying heat thresholds for South Africa towards the development of a heat-health warning system

Exposure to heatwaves may result in adverse human health impacts. Heat alerts in South Africa are currently based on defined temperature-fixed threshold values for large towns and cities. However, heat-health warning systems (HHWS) should incorporate metrics that have been shown to be effective predictors of negative heat-related health outcomes. This study contributes to the development of a HHWS for South Africa that can potentially minimize heat-related mortality. Distributed lag nonlinear models (DLNM) were used to assess the association between maximum and minimum temperature and diurnal temperature range (DTR) and population-adjusted mortality during summer months, and the effects were presented as incidence rate ratios (IRR). District-level thresholds for the best predictor from these three metrics were estimated with threshold regression. The mortality dataset contained records of daily registered deaths (n = 8,476,532) from 1997 to 2013 and data for the temperature indices were for the same period. Maximum temperature appeared to be the most statistically significant predictor of all-cause mortality with strong associations observed in 40 out of 52 districts. Maximum temperature was associated with increased risk of mortality in all but three of the districts. Our results also found that heat-related mortality was influenced by regional climate because the spatial distribution of the thresholds varied according to the climate zones across the country. On average, districts located in the hot, arid interior provinces of the Northern Cape and North West experienced some of the highest thresholds compared to districts located in temperate interior or coastal provinces. As the effects of climate change become more significant, population exposure to heat is increasing. Therefore, evidence-based HHWS are required to reduce heat-related mortality and morbidity. The exceedance of the maximum temperature thresholds provided in this study could be used to issue heat alerts as part of effective heat health action plans.

Using individual approach to examine the association between urban heat island and preterm birth: A nationwide cohort study in China

BACKGROUND

Evidence suggests that maternal exposure to heat might increase the risk of preterm birth (PTB), but no study has investigated the effect from urban heat island (UHI) at individual level.

AIMS

Our study aimed to investigate the association between individual UHI exposure and PTB.

METHODS

We utilized data from the ongoing China Birth Cohort Study (CBCS), encompassing 103,040 birth records up to December 2020. UHI exposure was estimated for each participant using a novel individual assessment method based on temperature data and satellite-derived land cover data. We used generalized linear mixed-effects models to estimate the association between UHI exposure and PTB, adjusting for potential confounders including maternal characteristics and environmental factors.

RESULTS

Consistent and statistically significant associations between UHI exposure and PTB were observed up to 21 days before birth. A 5 °C increment in UHI exposure was associated with 27 % higher risk (OR = 1.27, 95 % confident interval: 1.20, 1.34) of preterm birth in lagged day 1. Stratified analysis indicated that the associations were more pronounced in participants who were older, had higher pre-pregnancy body mass index level, of higher socioeconomic status and living in greener areas.

CONCLUSION

Maternal exposure to UHI was associated with increased risk of PTB. These findings have implications for developing targeted interventions for susceptible subgroups of pregnant women. More research is needed to validate our findings of increased risk of preterm birth due to UHI exposure among pregnant women.

Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China

BACKGROUND

There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden.

METHODS

Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status.

RESULTS

A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status.

CONCLUSIONS

Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.

The comparison of mortality burden between exposure to dry-cold events and wet-cold events: A nationwide study in China

BACKGROUND

Most previous studies have focused on the health effect of temperature or humidity, and few studies have explored the combined health effects of exposure to temperature and humidity. This study aims to estimate the relationship between humidity-cold events and mortality, and then to compare the mortality burden between exposure to dry-cold events and wet-cold events, and finally to explore whether there was an additive interaction of temperature and humidity on mortality.

METHODS

In the study, Daily mortality data during 2006-2017 were collected from Centers for Disease Control and Prevention in China, and daily mean temperature and daily mean relative humidity data from 698 weather stations in China were obtained from the China Meteorological Data Sharing Service system. We first employed time-series design with a distributed lag nonlinear model and a multivariate meta-analysis model to examine the association between humidity-cold events with mortality.

RESULTS

We found that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events (RR:1.24, 95%CI:1.20,1.29) was higher than that of dry-cold events (RR:1.14, 95%CI:1.10,1.18). Dry-cold events and wet-cold events accounted for 2.41 % and 2.99 % excess deaths, respectively with higher burden for the elderly ≥85 years old, Central China and CVD. In addition, there is a synergistic additive interaction between low temperature and high humidity in winter.

CONCLUSION

This study showed that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events was higher than that of dry-cold events.

The association of heatwave with drowning mortality in five provinces of China

Drowning is a serious public health problem in the world. Several studies have found that ambient temperature is associated with drowning, but few have investigated the effect of heatwave on drowning. This study aimed to explore the associations between heatwave and drowning mortality, and further estimate the mortality burden of drowning attributed to heatwave in China. Drowning mortality data were collected in 71 prefectures in China during 2013-2018 from provincial vital register system. Meteorological data at the same period were collected from European Centre for Medium-Range Weather Forecasts (ECMWF). A distributed lag non-linear model (DLNM) was first to explore the association between heatwave and drowning mortality in each prefecture. Secondly, the prefecture-specific associations were pooled using meta-analysis. Finally, attributable fractions (AFs) of drowning deaths caused by heatwave were estimated. Compared to normal day, the mortality risk of drowning significantly increased during heatwave (RR = 1.20, 95%CI: 1.18-1.23). Higher risks were observed in males (RR = 1.23, 95%CI: 1.20-1.27) than females (RR = 1.18, 95%CI: 1.13-1.23), in children aged 5-14 years old (RR = 1.24, 95%CI: 1.15-1.33) than other age groups, in urban city (RR = 1.32, 95%CI: 1.28-1.36) than rural area (RR = 1.09, 95%CI: 1.07-1.12) and in Jilin province (RR = 2.85, 95%CI: 1.61-5.06) than other provinces. The AF of drowning deaths due to heatwave was 11.4 % (95%CI: 10.0 %-12.9 %) during heatwave and 1.0 % (95%CI: 0.9 %-1.1 %) during study period, respectively. Moreover, the AFs during study period were higher for male (1.2 %, 95%CI: 1.0 %-1.3 %), children 5-14 years (1.1 %, 95%CI: 0.7 %-1.6 %), urban city (1.6 %, 95%CI: 1.4 %-1.8 %) than their correspondents. These differences were also observed in AFs during heatwave. We found that heatwave may significantly increase the mortality risk of drowning mortality, and its mortality burden attributable to heatwave was noteworthy. Targeted intervention should be carried out to decrease drowning mortality during heatwave.

Trade-offs between cold protection and air pollution-induced mortality of China's heating policy

The winter heating policy in northern China was designed to safeguard households from the harsh subfreezing temperatures. However, it has inadvertently resulted in seasonal spikes in air pollution levels because of the reliance on coal as an energy source. While the loss of life years attributable to mortality from air pollution caused by winter heating has been estimated, the beneficial effect of protection from cold temperatures has not been assessed, primarily due to a lack of individual-level data linking these variables. Our study aims to address this research gap. We provide individual-level empirical evidence that quantifies the impact of protection from cold temperatures and air pollution on mortality, studying 5,334 older adults living around the Huai River during the period between 2000 and 2018. Our adjusted Cox-proportional hazard models show that winter heating was associated with a 22% lower mortality rate (95% CI: 16-28%). Individuals residing in areas without access to winter heating are subjected to heightened mortality risks during periods of cold temperatures. The protective effect is offset by a 27.8% rise attributed to elevated PM2.5 levels. Our results imply that the equilibrium between the effects of these two factors is achieved when PM2.5 concentration exceeds 24.3 µg/m3 (95% CI: 18.4-30.2). Our research suggests that while the existing winter heating policy significantly mitigates winter mortality by lessening the detrimental effects of cold temperatures, future air pollution reduction could provide further health benefits.

A longitudinal study on the effect of extreme temperature on non-accidental deaths in Hulunbuir City based on DLNM model

OBJECTIVE

To explore the frequency and effect of extreme temperature on the non-accidental death rate in Hulunbuir, a Chinese ice city.

METHODS

From 2014 to 2018, mortality data of residents residing in Hulunbuir City were collected. The lag and cumulative effects of extreme temperature conditions on non-accidental death and respiratory and circulatory diseases were analyzed by distributed lag non-linear models (DLNM).

RESULTS

The risk of death was the highest during high-temperature conditions, the RR value was 1.111 (95% CI 1.031 ~ 1.198). The effect was severe and acute. The risk of death during extreme low-temperature conditions peaked on the fifth day, (RR 1.057; 95% CI 1.012 ~ 1.112), then decreased and was maintained for 12 days. The cumulative RR value was 1.289 (95% CI 1.045 ~ 1.589). Heat significantly influenced the incidence of non-accidental death in both men (RR 1.187; 95% CI 1.059-1.331) and women (RR 1.252; 95% CI 1.085-1.445).

CONCLUSIONS

Regardless of the temperature effect, the risk of death in the elderly group (≥ 65 years) was significantly higher than that of the young group (0-64 years). High-temperature and low-temperature conditions can contribute to the increased number of deaths in Hulunbei. While high-temperature has an acute effect, low-temperature has a lagging effect. Elderly and women, as well as people with circulatory diseases, are more sensitive to extreme temperatures.

Effect of short-term exposure to ambient air pollutants on non-accidental mortality in emergency department visits: a time-series study

Objectives

Exposure to air pollution has been linked to an increased risk of premature mortality. However, the acute effects of air pollution on the risk of non-accidental mortality have not been extensively researched in developing countries, and the findings thus far have been inconsistent. Therefore, this study aimed to examine the association between short-term exposure to six pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) and non-accidental mortality in Beijing, China.

Methods

Daily data on non-accidental deaths were gathered from 1 January 2017 to 31 December 2018. Air pollution data for the same period were collected from 35 fixed-site air quality monitoring stations in Beijing. Generalized additive models (GAM) based on Poisson regression were used to investigate the association between non-accidental mortality in emergency department visits and the daily average levels of air pollutants.

Results

There were 8,676 non-accidental deaths recorded during 2017-2018. After sensitivity analysis, short-term exposure to air pollutants, particularly gaseous pollutants, was linked to non-accidental mortality. Specifically, for every 10 μg/m³ increase (5 μg/m³ in SO₂, 0.5 mg/m³ in CO) of SO₂ (lag 04), NO₂ (lag 04), O₃ (lag 05), and CO (lag 04), the relative risk (RR) values were 1.054 (95% CI: 1.009, 1.100), 1.038 (95% CI: 1.013, 1.063), 1.032 (95% CI: 1.011, 1.054), and 1.034 (95% CI: 1.004, 1.066), respectively. In terms of causes of death, short-term exposure to NO₂, SO₂, and O₃ increased the risk of circulatory mortality. Further stratified analysis revealed that the stronger associations were presented in females for O₃ while in males for CO. People aged 65 and over were strongly associated with ambient air pollution.

Conclusions

Our study showed that ambient air pollutants were associated with non-accidental mortality. Our findings suggested that efforts to control gaseous pollution should be stepped up, and vulnerable groups should be the focus of health protection education.

Short-term exposure to temperature and mental health in North Carolina: a distributed lag nonlinear analysis

Adverse mental health outcomes have been associated with high temperatures in studies worldwide. Few studies explore a broad range of mental health outcomes, and to our knowledge, none are specific to NC, USA. This ecological study explored the relationship between ambient temperature and mental health outcomes (suicide, self-harm and suicide ideation, anxiety and stress, mood disorders, and depression) in six urban counties across the state of NC, USA. We applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM) to examine the short-term effects of daily ambient temperature on emergency admissions for mental health conditions (2016 to 2018) and violent deaths (2004 to 2018). The results were predominately insignificant, with some key exceptions. The county with the greatest temperature range (Wake) displays higher levels of significance, while counties with the lowest temperature ranges (New Hanover and Pitt) are almost entirely insignificant. Self-harm and suicidal ideation peak in the warm months (July) and generally exhibit a protective effect at lower temperatures and shorter lag intervals. Whereas anxiety, depression, and major depressive disorders peak in the cooler months (May and September). Suicide is the only outcome that favored a 20-day lag period in the sensitivity analysis, although the association with temperature was insignificant. Our findings suggest additional research is needed across a suite of mental health outcomes to fully understand the effects of temperatures on mental health.

A novel mathematical model for estimating the relative risk of mortality attributable to the combined effect of ambient fine particulate matter (PM2.5) and cold ambient temperature

Exposures to ambient fine particulate matter (PM_2.5) and cold ambient temperatures have been identified as important risk factors in contributing towards the global mortality from chronic obstructive pulmonary disease (COPD). Despite China currently being the country with the largest population in the world, previous relative risk (RR) models have considered little or no information from the ambient air pollution related cohort studies in the country. This likely provides a less accurate picture of the trend in air pollution attributable mortality in the country over time. A novel relative risk model called pollutant-temperature exposure (PTE) model is proposed to estimate the RR attributable to the combined effect of air pollution and ambient temperature in a population. In this paper, the pollutant concentration-response curve was extrapolated from the cohort studies in China, whereas the temperature response curve was extracted from a study in Yangtze River Delta (YRD) region. The performance of the PTE model was compared with the integrated exposure-response (IER) model using the data of YRD region, which revealed that the estimated relative risks of the PTE model were noticeably higher than the IER model during the winter season. Furthermore, the predictive ability of the PTE model was validated using actual data of Ningbo city, which showed that the estimated RR using the PTE model with 1-month moving average data showed a good result with the trend of actual COPD mortality, indicated by a lower root mean square error (RMSE = 0.956). By considering the combined effect of ambient air pollutant and ambient temperature, the PTE model is expected to provide more accurate relative risk estimates for the regions with high levels of ambient PM_2.5 and seasonal variation of ambient temperature.

Exposure-response relationship between temperature, relative humidity, and varicella: a multicity study in South China

Varicella is a rising public health issue. Several studies have tried to quantify the relationships between meteorological factors and varicella incidence but with inconsistent results. We aim to investigate the impact of temperature and relative humidity on varicella, and to further explore the effect modification of these relationships. In this study, the data of varicella and meteorological factors from 2011 to 2019 in 21 cities of Guangdong Province, China were collected. Distributed lag nonlinear models (DLNM) were constructed to explore the relationship between meteorological factors (temperature and relative humidity) and varicella in each city, controlling in school terms, holidays, seasonality, long-term trends, and day of week. Multivariate meta-analysis was applied to pool the city-specific estimations. And the meta-regression was used to explore the effect modification for the spatial heterogeneity of city-specific meteorological factors and social factors (such as disposable income per capita, vaccination coverage, and so on) on varicella. The results indicated that the relationship between temperature and varicella in 21 cities appeared nonlinear with an inverted S-shaped. The relative risk peaked at 20.8 ℃ (RR = 1.42, 95% CI: 1.22, 1.65). The relative humidity-varicella relationship was approximately L-shaped, with a peaking risk at 69.5% relative humidity (RR = 1.25, 95% CI: 1.04, 1.50). The spatial heterogeneity of temperature-varicella relationships may be caused by income or varicella vaccination coverage. And varicella vaccination coverage may contribute to the spatial heterogeneity of the relative humidity-varicella relationship. The findings can help us deepen the understanding of the meteorological factors-varicella association and provide evidence for developing prevention strategy for varicella epidemic.

Mortality burden attributable to temperature variability in China

BACKGROUND

Several studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce.

OBJECTIVES

To investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China.

METHODS

We calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV.

RESULTS

U-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment.

SIGNIFICANCE

Our findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability.

IMPACT

(1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.

Regional incidence risk of heat stroke in elderly individuals considering population, household structure, and local industrial sector

This study aims to clarify the regional characteristics of heat stroke incidence patterns inside and outside residences among the elderly from the perspective of working and living conditions. The study area comprised 41 municipalities belonging to Hyogo Prefecture in Japan. Based on information on heat stroke emergency medical evacuees in each municipality from 2011 to 2020, the regional differences in the incidence risk of heat stroke were analyzed. The results revealed that the number of cases and the proportion of males and females among them were related to the demographic structure of each municipality. A grouping analysis was conducted to classify the characteristics of each municipality based on the relationship between the incidence risk of heat stroke and the industrial structure. A factor analysis and binomial logistic regression analysis were also conducted to investigate the effect of demographic structure on the incidence risk of heat stroke. The results indicate that the incidence risk of heat stroke is correlated with industrial and demographic structures, and the risk is likely to vary regionally.

An analysis of past and future heatwaves based on a heat-associated mortality threshold: towards a heat health warning system

Heatwaves can have severe impacts on human health extending from illness to mortality. These health effects are related to not only the physical phenomenon of heat itself but other characteristics such as frequency, intensity, and duration of heatwaves. Therefore, understanding heatwave characteristics is a crucial step in the development of heat-health warning systems (HHWS) that could prevent or reduce negative heat-related health outcomes. However, there are no South African studies that have quantified heatwaves with a threshold that incorporated a temperature metric based on a health outcome. To fill this gap, this study aimed to assess the spatial and temporal distribution and frequency of past (2014 - 2019) and future (period 2020 - 2039) heatwaves across South Africa. Heatwaves were defined using a threshold for diurnal temperature range (DTR) that was found to have measurable impacts on mortality. In the current climate, inland provinces experienced fewer heatwaves of longer duration and greater intensity compared to coastal provinces that experienced heatwaves of lower intensity. The highest frequency of heatwaves occurred during the austral summer accounting for a total of 150 events out of 270 from 2014 to 2019. The heatwave definition applied in this study also identified severe heatwaves across the country during late 2015 to early 2016 which was during the strongest El Niño event ever recorded to date. Record-breaking global temperatures were reported during this period; the North West province in South Africa was the worst affected experiencing heatwaves ranging from 12 to 77 days. Future climate analysis showed increasing trends in heatwave events with the greatest increases (80%-87%) expected to occur during summer months. The number of heatwaves occurring in cooler seasons is expected to increase with more events projected from the winter months of July and August, onwards. The findings of this study show that the identification of provinces and towns that experience intense, long-lasting heatwaves is crucial to inform development and implementation of targeted heat-health adaptation strategies. These findings could also guide authorities to prioritise vulnerable population groups such as the elderly and children living in high-risk areas likely to be affected by heatwaves.

Climate change and city size: the role of temperature difference in the spatial distribution of China's population

This paper examines the relationship between climate change and the spatial distribution of population in China. We establish a two-way fixed effects model to investigate the role of temperature difference in the spatial distribution of China's population. We find that the annual variation of temperature has an impact on city size in both large and small cities, and that city size tends to shrink as the temperature difference increases. Meanwhile, we also find that the population in the cities located south of Qinling-Huaihe Line and Aihui-Tengchong Line (Hu's Line) is more sensitive to temperature effects, and that the temperature difference has a significant negative effect on city size. Similarly, the same results are found for prefecture-level cities with low administrative levels. Considering the endogeneity between temperature change and city size, we adopt an instrumental variable using latitude to perform a more robust empirical analysis, the results of a series of robustness tests support these conclusions.

The effects of temperature variability on mortality in patients with chronic obstructive pulmonary disease: a time-series analysis in Hangzhou, China

Chronic obstructive pulmonary disease (COPD) is a leading cause of death in people aged over 60 years old. Research has been reported that ambient temperature and diurnal temperature range (DTR), as representative indices of temperature variability, are contributors to the development and exacerbation of COPD. However, few studies are available in Chinese population. In this study, we aimed to assess the associations of temperature variability on COPD mortality in a fast developing city in China. Using the mortality surveillance system, we obtained a total of 7,863 deaths attributed to COPD from 2014 to 2016. Quasi-Poisson generalized linear regression with distributed lag non-linear model was applied to explore the associations between temperature variability and COPD deaths, after controlling for the potential confounders, including relative humidity, day of week, public holiday, and long-term trend. A J-shaped association of DTR and a reversely J-shaped association of temperature for COPD mortality were observed. Risk estimates showed that the relative risks (RRs) of COPD mortality with extreme high DTR at lag 0 and 0-7 days were 1.045 (95% CI: 0.949-1.151) and 1.460 (95% CI: 1.118-1.908), and the extreme high temperature at lag 0 and 0-7 days were 1.090 (95% CI: 0.945-1.256) and 1.352 (95% CI: 1.163-1.572). Our findings suggest that short-term exposure to extreme temperature was associated with mortality for COPD in Hangzhou. The evidence has implications for policy decision-making and targeted interventions.

Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019

BACKGROUND

Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.

METHODS

The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.

FINDINGS

We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.

INTERPRETATION

A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.

FUNDING

National Key Research and Development Program.

The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities

Background

Physical activity is an important factor in premature mortality reduction, non-communicable disease prevention, and well-being protection. Climate change will alter temperatures globally, with impacts already found on mortality and morbidity. While uncomfortable temperature is often perceived as a barrier to physical activity, the actual impact of temperature on physical activity has been less well studied, particularly in China. This study examined the associations between temperature and objectively measured physical activity among adult populations in five major Chinese cities.

Methods

Aggregated anonymized step count data was obtained between December 2017-2018 for five major Chinese cities: Beijing, Shanghai, Chongqing, Shenzhen, and Hong Kong. The associations of temperature with daily aggregated mean step count were assessed using Generalized Additive Models (GAMs), adjusted for meteorological, air pollution, and time-related variables.

Results

Significant decreases in step counts during periods of high temperatures were found for cold or temperate climate cities (Beijing, Shanghai, and Chongqing), with maximum physical activity occurring between 16 and 19.3 °C. High temperatures were associated with decreases of 800-1500 daily steps compared to optimal temperatures. For cities in subtropical climates (Shenzhen and Hong Kong), non-significant declines were found with high temperatures. Overall, females and the elderly demonstrated lower optimal temperatures for physical activity and larger decreases of step count in warmer temperatures.

Conclusions

As minor reductions in physical activity could consequentially affect health, an increased awareness of temperature’s impact on physical activity is necessary. City-wide adaptations and physical activity interventions should seek ways to sustain physical activity levels in the face of shifting temperatures from climate change.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01285-1.

Time series study on the effects of daily average temperature on the mortality from respiratory diseases and circulatory diseases: a case study in Mianyang City

Background

Climate change caused by environmental pollution is the most important one of many environmental health hazards currently faced by human beings. In particular, the extreme temperature is an important risk factor for death from respiratory and circulatory diseases. This study aims to explore the meteorological-health effect and find out the vulnerable individuals of extreme temperature events in a less developed city in western China.

Method

We collected the meteorological data and data of death caused by respiratory and circulatory diseases in Mianyang City from 2013 to 2019. The nonlinear distributed lag model and the generalized additive models were combined to study the influence of daily average temperature (DAT) on mortality from respiratory and circulatory diseases in different genders, ages.

Results

The exposure-response curves between DAT and mortality from respiratory and circulatory diseases presented a nonlinear characteristic of the “V” type. Cumulative Relative Risk of 30 days (CRR₃₀) of deaths from respiratory diseases with 4.48 (2.98, 6.73) was higher than that from circulatory diseases with 2.77 (1.96, 3.92) at extremely low temperature, while there was no obvious difference at extremely high temperature. The health effects of low temperatures on the respiratory system of people of all ages and genders were persistent, while that of high temperatures were acute and short-term. The circulatory systems of people aged < 65 years were more susceptible to acute effects of cold temperatures, while the effects were delayed in females and people aged ≥65 years.

Conclusion

Both low and high temperatures increased the risk of mortality from respiratory and circulatory diseases. Cold effects seemed to last longer than heat did.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13384-6.

Health risk of extreme low temperature on respiratory diseases in western China

Previous studies have reported that daily average temperature is connected with respiratory diseases (RD), but proof is limited for the influence of the extreme low temperature on RD in Lanzhou, a northwestern China of temperate area. Generalized additive model (GAM) was built in this work to describe the relationship between daily mean temperature and RD in Lanzhou, China from 2012 to 2017. The results indicated that the exposure-response curve was inverse J-shaped, showing the lower the temperature, the larger the relative risk (RR). The RR of daily emergency room (ER) admissions in P5 extreme low temperature (the temperature below the fifth percentile, etc.) was larger than that in P10. The P5 extreme low temperature has the strongest effect at lag 0, and the RRs were 1.043 (95% CI: 1.030, 1.055) for the total, 1.031 (95% CI: 1.015, 1.046) for males and 1.058 (95% CI: 1.039, 1.077) for females. For different age groups, the largest RRs were 1.026 (95% CI: 1.013, 1.039) for the children (age < 16 years) at lag 5, 1.057 (95% CI: 1.030, 1.085) for the young adults (aged 16-45 years), 1.060 (95% CI: 1.023, 1.099) for the middle-aged (aged 46-60 years) and 1.121 (95% CI: 1.077, 1.166) for the elderly group of age > 60 years. Meanwhile, females and the elderly were more vulnerable to extreme temperature. The results could strengthen the scientific evidence of effects of extreme low temperature on RD in temperate areas.

The effect of ambient temperature on in-hospital mortality: a study in Nanjing, China

To reduce the inpatient mortality and improve the quality of hospital management, we explore the relationship between temperatures and in-hospital mortality in a large sample across 10 years in Nanjing, Jiangsu. We collected 10 years’ data on patient deaths from a large research hospital. Distributed lag non-linear model (DLNM) was used to find the association between daily mean temperatures and in-hospital mortality. A total of 6160 in-hospital deaths were documented. Overall, peak RR appeared at 8 °C, with the range of 1 to 20 °C having a significantly high mortality risk. In the elderly (age ≥ 65 years), peak RR appeared at 5 °C, with range − 3 to 21 °C having a significantly high mortality risk. In males, peak RR appeared at 8 °C, with the range 0 to 24 °C having a significantly high mortality risk. Moderate cold (define as 2.5th percentile of daily mean temperatures to the MT), not extreme temperatures (≤ 2.5th percentile or ≥ 97.5th percentile of daily mean temperatures), increased the risk of death in hospital patients, especially in elderly and male in-hospital patients.

Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China

Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.

Investigating age and regional effects on the relation between the incidence of heat-related ambulance transport and daily maximum temperature or WBGT

Background

Although age and regional climate are considered to have effects on the incidence ratio of heat-related illness, quantitative estimation of age or region on the effect of occurring temperature for heat stroke is limited.

Methods

By utilizing data on the number of daily heat-related ambulance transport (HAT) in each of three age groups (7–17, 18–64, 65 years old, or older) and 47 prefectures in Japan, and daily maximum temperature (DMT) or Wet Bulb Globe Temperature (DMW) of each prefecture for the summer season, the effects of age and region on heat-related illness were studied. Two-way ANOVA was used to analyze the significance of the effect of age and 10 regions in Japan on HAT. The population-weighted average of DMT or DMW measured at weather stations in each prefecture was used as DMT or DMW for each prefecture. DMT or DMW when HAT is one in 100,000 people (T₁ and W₁, respectively) was calculated for each age category and prefecture as an indicator of heat acclimatization. The relation between T₁ or W₁ and average DMT or DMW of each age category and prefecture were also analyzed.

Results

HAT of each age category and prefecture was plotted nearly on the exponential function of corresponding DMT or DMW. Average R² of the regression function in 47 prefectures in terms of DMW was 0.86, 0.93, and 0.94 for juveniles, adults, and elderly, respectively. The largest regional difference of W₁ in 47 prefectures was 4.5 and 4.8 °C for juveniles and adults, respectively between Hokkaido and Tokyo, 3.9 °C for elderly between Hokkaido and Okinawa. Estimated W₁ and average DMT or DMW during the summer season for 47 prefectures was linearly related. Regarding age difference, the regression line showed that W₁ of the prefecture for DMW at 30 °C of WBGT was 31.1 °C, 32.4 °C, and 29.8 °C for juveniles, adults, and elderly, respectively.

Conclusions

Age and regional differences affected the incidence of HAT. Thus, it is recommended that public prevention measures for heat-related disorders take into consideration age and regional variability.

Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden

Although studies have investigated the associations between PM_2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM_2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014–2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM_2.5 (lag 0–3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 μg/m³ increment in PM_2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM_2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [−0.60%, 1.84%]). Disparities in PM_2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM_2.5 with mortality risks in China and demonstrated urban-rural disparities of PM_2.5-mortality associations for various causes of death.

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PM_2.5 had greater effects on CVD/CED mortality in urban cities than in rural areas

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PM_2.5 had stronger effects on RESP mortality in rural areas than in urban cities

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An annual mean of 16.5/100,000 deaths was attributable to PM_2.5 in urban cities

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An annual mean of 3.4//100,000 deaths was attributable to PM_2.5 in rural areas

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Spatially targeted measures are needed to reduce PM_2.5-related mortality in China

Contamination of drinking water by neonicotinoid insecticides in China: Human exposure potential through drinking water consumption and percutaneous penetration

Neonicotinoids (NEOs) are the most widely used pesticides and have posed a serious threat to human health. However, data on human exposure to NEOs are extremely scarce. To bridge this gap, human exposure potential of NEOs through drinking water consumption and percutaneous penetration was evaluated with the influences of 17 age groups, 4 seasons, 6 regions, and 2 genders. The results showed that drinking water in the present study had an upper middle level of NEO contamination. Anthropogenic activity and weather condition played important roles in the regional distribution of NEOs in tap water. For both children and adults, NEOs intake from drinking water exposure (NDE) and percutaneous exposure (NPE) in the south regions of China are significantly higher than those in the north regions, while the order of NDE and NPE by season is summer > spring = autumn > winter. Furthermore, human age and gender also have remarkable impacts on NDE and NPE. The age groups of children subjected to the highest NDE and NPE were 9 months - 2 years old and 9-12 years old, respectively. This study provides insights into the role of seasonal and regional influence, age and gender in the risk of drinking water and percutaneous exposure to NEOs.

Daily ambient temperature and mortality in Thailand: Estimated effects, attributable risks, and effect modifications by greenness

BACKGROUND

In recent years, many previous studies have examined the association between ambient temperature and mortality in different parts of the world. However, very few studies have explored the mortality burden attributable to temperature, especially those in developing countries. This study aimed to quantify the burden of mortality attributable to non-optimum temperature in Thailand and explore whether greenness, using normalized difference vegetation index (NDVI) as indicator, alleviates the mortality contributed by non-optimum ambient temperature.

METHODS

Daily number of mortality (i.e., all-cause, cardiovascular and respiratory diseases) and daily meteorological data were obtained over 65 provinces in Thailand during 2010 to 2017. The two-stage statistical approach was applied to estimate the association between temperature and mortality. First, the time-stratified case-crossover analysis was performed to examine province-specific temperature-mortality association. Second, province-specific association was pooled to derive national estimates using multivariate meta-regression. Mortality burden attributable to temperature was then estimated, and the association between attributed mortality and NDVI was explored using multivariate meta-regression models.

RESULTS

A total of 2,891,407 all-cause of death was included over the study period, in which 403,450 and 264,672 deaths were accounted for cardiovascular and respiratory diseases, respectively. The temperature-mortality association at cumulative lag 0-7 days was non-linear with J-shaped curve for all-cause and respiratory mortality, whereas V-shaped curve was observed for cardiovascular mortality. Using minimum mortality temperature (MMT) as optimum temperature, 3.72% (95% empirical CI: 2.18, 5.21) of all-cause, 2.92% (0.55, 5.10) of cardiovascular and 3.00% (0.27, 5.49) of respiratory mortality were attributable to non-optimum temperature (both hot and cold effects). Higher level of NDVI was associated with alleviated impacts of non-optimum temperature, especially hot temperature.

CONCLUSION

Exposure to non-optimum temperature was associated with increased risks of mortality in Thailand. This finding is useful for planning the public health interventions to reduce health effects of non-optimum ambient temperature.

Short-term effect of NO2 on outpatient visits for dermatologic diseases in Xinxiang, China: a time-series study

OBJECTIVES

As the largest organ of the human body, the skin is the major exposure route of NO₂. However, the evidence for a relationship between NO₂ exposure and dermatologic diseases (DMs) is limited. This time-series study was conducted to assess the short-term effect of nitrogen dioxide (NO₂) exposure on DMs outpatient visits in Xinxiang, China.

METHODS

Daily recordings of NO₂ concentrations, meteorological data, and the outpatient visits data for DMs were collected in Xinxiang from January 1st, 2015, to December 31st, 2018. The analysis method used was based on the generalized additive model (GAM) with quasi-Poisson regression to investigate the relationship between NO₂ exposure and DMs outpatient visits. Several covariates, such as long-term trends, seasonality, and weather conditions were controlled.

RESULTS

A total of 164,270 DMs outpatients were recorded. A 10 μg/m³ increase in NO₂ concentrations during the period was associated with a 1.86% increase in DMs outpatient visits (95% confidence intervals [Cl]: 1.06-2.66%). The effect was stronger (around 6 times) in the cool seasons than in warmer seasons and younger patients (< 15 years of age) appeared to be more vulnerable.

CONCLUSIONS

The findings of this study indicate that short-term exposure to NO₂ increases the risk of DMs in Xinxiang, China, especially in the cool seasons. Policymakers should implement more stringent air quality standards to improve air quality.

High ambient temperature exposure during late gestation disrupts glycolipid metabolism and hepatic mitochondrial function tightly related to gut microbial dysbiosis in pregnant mice

As global warming intensifies, emerging evidence has demonstrated high ambient temperature during pregnancy negatively affects maternal physiology with compromised pregnant outcomes; however, little is known about the roles of gut microbiota and its underlying mechanisms in this process. Here, for the first time, we explored the potential mechanisms of gut microbiota involved in the disrupted glycolipid metabolism via hepatic mitochondrial function. Our results indicate heat stress (HS) reduces fat and protein contents and serum levels of insulin and triglyceride (TG), while increases that of non-esterified fatty acid (NEFA), β-hydroxybutyric acid (B-HBA), creatinine and blood urea nitrogen (BUN) (P < 0.05). Additionally, HS downregulates both mitochondrial genes (mtDNA) and nuclear encoding mitochondrial functional genes with increasing serum levels of malondialdehyde (MDA) and 8-hydroxydeoxyguanosine (8-OHdG) (P < 0.05). Regarding microbial response, HS boosts serum levels of lipopolysaccharide (LPS) (P < 0.05) and alters β-diversity (ANOSIM, P < 0.01), increasing the proportions of Escherichia-Shigella, Acinetobacter and Klebsiella (q < 0.05), while reducing that of Ruminiclostridium, Blautia, Lachnospiraceae_NK4A136_group, Clostridium VadinBB60 and Muribaculaceae (q < 0.05). PICRUSt analysis predicts that HS upregulates 11 KEGG pathways, mainly including bile secretion and bacterial invasion of epithelial cells. The collective results suggest that microbial dysbiosis due to late gestational HS has strong associations with damaged hepatic mitochondrial function and disrupted metabolic profiles.

Mapping China’s Electronic Power Consumption Using Points of Interest and Remote Sensing Data

Producing gridded electric power consumption (EPC) maps at a fine geographic scale is critical for rational deployment and effective utilization of electric power resources. Brightness of nighttime light (NTL) has been extensively adopted to evaluate the spatial patterns of EPC at multiple geographical scales. However, the blooming effect and saturation issue of NTL imagery limit its ability to accurately map EPC. Moreover, limited sectoral separation in applying NTL leads to the inaccurate spatial distribution of EPC, particularly in the case of industrial EPC, which is often a dominant portion of the total EPC in China. This study pioneers the separate estimation of spatial patterns of industrial and nonindustrial EPC over mainland China by jointly using points of interest (POIs) and multiple remotely sensed data in a random forests (RF) model. The POIs provided fine and detailed information about the different socioeconomic activities and played a significant role in determining industrial and nonindustrial EPC distribution. Based on the RF model, we produced industrial, non-industrial, and overall EPC maps at a 1 km resolution in mainland China for 2011. Compared against statistical data at the county level, our results showed a high accuracy (R2 = 0.958 for nonindustrial EPC estimation, 0.848 for industrial EPC estimation, and 0.913 for total EPC). This study indicated that the proposed RF-based method, integrating POIs and multiple remote sensing data, can markedly improve the accuracy for estimating EPC. This study also revealed the great potential of POIs in mapping the distribution of socioeconomic parameters.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data

BACKGROUND

Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions.

METHODS

Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature.

RESULTS

A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier.

CONCLUSIONS

The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

Ambient Temperature and Years of Life Lost: A National Study in China

Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013–2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006–2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65–74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics.

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Years of life lost (YLL) is used to estimate the effects of temperature

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Both low and high temperatures can increase the YLLs

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Average 1.02 YLL per death is attributed to temperature exposure

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Temperature causes larger YLLs per death in males, younger people, and central China

Life loss of cardiovascular diseases per death attributable to ambient temperature: A national time series analysis based on 364 locations in China

BACKGROUND

Although the effect of ambient temperature on cardiovascular disease (CVDs) has been well explored, studies using years of life lost (YLLs) as the outcome especially evaluating the average life loss per death attributable to temperatures were rare. We examine the associations between ambient temperature and YLLs of CVDs, and further quantify temperature-related life loss per death.

METHODS

Daily YLL rates were calculated using death data from 364 locations across China during 2006-2017, and meteorological data were collected for the same period. A distributed-lag nonlinear model and meta-regression were applied to examine the relationships between temperature and YLL rates of CVDs. Subgroup analyses by age, gender, region, and cause-specific CVDs were investigated. The total YLLs and average YLLs per death attributable to temperature were further quantified to assess life loss caused by non-optimal temperature.

RESULTS

Both high and low temperatures significantly increased YLL rates of CVDs, with greater effects for cold than heat. Cerebrovascular diseases (CEDs) account for the largest proportion (47.17%) of total YLLs of CVDs attributable to non-optimal temperature. On average, life loss per CVD death attributable to non-optimal temperatures was 1.51 (95% eCI: 1.33, 1.69) years, with 1.07 (95% eCI: 1.00, 1.15) years from moderate cold. Average life losses per death were observed higher for males (1.71, 95% eCI: 1.43, 1.99), younger population (3.82, 95% eCI: 2.86, 4.75), central China (1.62; 95% eCI: 1.41, 1.83) and hemorrhagic stroke (2.86, 95% eCI: 2.63, 3.10) than their correspondents.

CONCLUSIONS

We found that non-optimal temperature significantly aggravated premature death of CVD, with CEDs being the most affected, and most of temperature-related life loss of CVD was attributed to moderate cold. Our findings imply that peoples with CEDs in moderate cold days are vulnerable populations, which may contribute to a better understanding the adverse effects and pathogenesis of temperature on CVDs.

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis

Background

The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19.

Methods

The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China.

Results

During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust.

Conclusions

The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.

The Mortality Risk and Socioeconomic Vulnerability Associated with High and Low Temperature in Hong Kong

(1) Background: The adverse health effect associated with extreme temperature has been extensively reported in the current literature. Some also found that temperature effect may vary among the population with different socioeconomic status (SES), but found inconsistent results. Previous studies on the socioeconomic vulnerability of temperature effect were mainly achieved by multi-city or country analysis, but the large heterogeneity between cities may introduce additional bias to the estimation. The linkage between death registry and census in Hong Kong allows us to perform a city-wide analysis in which the study population shares virtually the same cultural, lifestyle and policy environment. This study aims to examine and compare the high and low temperature on morality in Hong Kong, a city with a subtropical climate and address a key research question of whether the extreme high and low temperature disproportionally affects population with lower SES. (2) Methods: Poisson-generalized additive models and distributed-lagged nonlinear models were used to examine the association between daily mortality and daily mean temperature between 2007–2015 with other meteorological and confounding factors controlled. Death registry was linked with small area census and area-level median household income was used as the proxy for socioeconomic status. (3) Results: 362,957 deaths during the study period were included in the analysis. The minimum mortality temperature was found to be 28.9 °C (82nd percentile). With a subtropical climate, the low temperature has a stronger effect than the high temperature on non-accidental, cardiovascular, respiratory and cancer deaths in Hong Kong. The hot effect was more pronounced in the first few days, while cold effect tended to last up to three weeks. Significant heat effect was only observed in the lower SES groups, whilst the extreme low temperature was associated with significantly higher mortality risk across all SES groups. The older population were susceptible to extreme temperature, especially for cold. (4) Conclusions: This study raised the concern of cold-related health impact in the subtropical region. Compared with high temperature, low temperature may be considered a universal hazard to the entire population in Hong Kong rather than only disproportionally affecting people with lower SES. Future public health policy should reconsider the strategy at both individual and community levels to reduce temperature-related mortality.

Comparison of life loss per death attributable to ambient temperature among various development regions: a nationwide study in 364 locations in China

BACKGROUND

Several studies have investigated the associations between ambient temperature and years of life lost (YLLs), but few focused on the difference of life loss attributable to temperature among different socioeconomic development levels.

OBJECTIVES

We investigated the disparity in temperature-YLL rate relationships and life loss per death attributable to nonoptimal temperature in regions with various development levels.

METHODS

Three hundred sixty-four Chinese counties or districts were classified into 92 high-development regions (HDRs) and 272 low-development regions (LDRs) according to socioeconomic factors of each location using K-means clustering approach. We used distributed lag non-linear models (DLNM) and multivariate meta-analysis to estimate the temperature-YLL rate relationships. We calculated attributable fraction (AF) of YLL and temperature-related average life loss per death to compare mortality burden of temperature between HDRs and LDRs. Stratified analyses were conducted by region, age, sex and cause of death.

RESULTS

We found that non-optimal temperatures increased YLL rates in both HDRs and LDRs, but all subgroups in LDRs were more vulnerable. The disparity of cold effects between HDRs and LDRs was significant, while the difference in heat effect was insignificant. The overall AF of non-optimal temperature in LDRs [AF = 12.2, 95% empirical confidence interval (eCI):11.0-13.5%] was higher than that in HDRs (AF = 8.9, 95% eCI: 8.3-9.5%). Subgroups analyses found that most groups in LDRs had greater AFs than that in HDRs. The average life loss per death due to non-optimal temperature in LDRs (1.91 years, 95% eCI: 1.72-2.10) was also higher than that in HDRs (1.32 years, 95% eCI: 1.23-1.41). Most of AFs and life loss per death were caused by moderate cold in both HDRs and LDRs.

CONCLUSIONS

Mortality burden caused by temperature was more significant in LDRs than that in HDRs, which means that more attention should be paid to vulnerable populations in LDRs in planning adaptive strategies.

Relationship between different particle size fractions and all-cause and cause-specific emergency ambulance dispatches

BACKGROUND

Evidence on the relationship between different particle size fractions and emergency ambulance dispatches (EAD) remains limited and sparse.

METHODS

We collected daily data of EAD, ambient air pollution and meteorological data from 2014 to 2018 in Guangzhou, China. We used a generalized additive model with covariate adjustments to estimate the associations between different particle size fractions and EAD related to all-cause, cardiovascular diseases, and respiratory diseases. Several subgroup and sensitivity analyses were also performed.

RESULTS

Significant associations were observed between PM_2.5, PM_2.5-10, PM₁₀ and EADs. A 10 μg/m³ increase of PM_2.5, PM_2.5-10, and PM₁₀ was associated with an increase of 0.98% (95% CI: 0.67, 1.28%), 2.06% (95% CI: 1.44, 2.68%), and 0.75% (95%CI: 0.53, 0.96%) in all-cause EAD, with an increase of 0.69% (95% CI: 0.00, 1.39%), 2.04% (95% CI: 0.64, 3.45%), and 0.60% (95%CI: 0.11,1.10%) in cardiovascular-related EAD, and an increase of 1.14% (95% CI: 0.25, 2.04%), 2.52% (95% CI: 0.72, 4.35%), and 0.89% (95%CI: 0.25,1.52%) in respiratory-related EAD at lag03, respectively. The results were robust in subgroup and sensitivity analyses.

CONCLUSIONS

This study revealed that PM_2.5, PM_2.5-10 and PM₁₀ were significantly related with risks of all-cause and cause-specific EAD. More evidence of high quality may be needed to further support our results in this ecological study.

The association between ambient temperature and clinical visits for inflammation-related diseases in rural areas in China

BACKGROUND

The association between temperature and mortality has been widely reported. However, it remains largely unclear whether inflammation-related diseases, caused by excessive or inappropriate inflammatory reaction, may be affected by ambient temperature, particularly in low-income areas.

OBJECTIVES

To explore the association between ambient temperature and clinical visits for inflammation-related diseases in rural villages in the Ningxia Hui Autonomous Region, China, during 2012─2015.

METHODS

Daily data on inflammation-related diseases and weather conditions were collected from 258 villages in Haiyuan (161 villages) and Yanchi (97 villages) counties during 2012─2015. A Quasi-Poisson regression with distributed lag non-linear model was used to examine the association between temperature and clinical visits for inflammation-related diseases. Stratified analyses were performed by types of diseases including arthritis, gastroenteritis, and gynecological inflammations.

RESULTS

During the study period, there were 724,788 and 288,965 clinical visits for inflammation-related diseases in Haiyuan and Yanchi, respectively. Both exposure to low (RR: 2.045, 95% CI: 1.690, 2.474) and high temperatures (RR: 1.244, 95% CI: 1.107, 1.399) were associated with increased risk of total inflammation-related visits in Haiyuan county. Low temperatures were associated with increased risks of all types of inflammation-related diseases in Yanchi county (RR: 4.344, 95% CI: 2.887, 6.535), while high temperatures only affected gastroenteritis (RR: 1.274, 95% CI: 1.040, 1.561). Moderate temperatures explained approximately 26% and 33% of clinical visits due to inflammation-related diseases in Haiyuan and Yanchi, respectively, with the burden attributable to cold exposure higher than hot exposure. The reference temperature values ranged from 17 to 19 in Haiyuan, and 12 to 14 in Yanchi for all types of clinical visits.

CONCLUSIONS

Our findings add additional evidence for the adverse effect of suboptimal ambient temperature and provide useful information for public health programs targeting people living in rural villages.

Short-term effects of diurnal temperature range on hospital admission in Bangkok, Thailand

Diurnal temperature range (DTR) is a key indicator reflecting climate stability. Many previous studies have examined the effects of ambient temperature, both hot and cold, on human morbidity and mortality, but few studies have evaluated health effects of DTR, especially those in developing countries. This study aimed to investigate the association between short-term exposure to DTR and hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand. We obtained daily meteorological variables from the Thai Meteorological Department from January 2006 through December 2014 and daily hospital admissions from the National Health Security Office during the same period. Quasi-Poisson generalized linear regression model combined with distributed lag non-linear model was used to examine the association between DTR and cardiovascular and respiratory hospital admissions controlling for daily average temperature, relative humidity, day of the week, public holiday, and seasonal and long-term trend. A J-shape relationship between DTR and hospital admissions was observed. With 7.8 °C DTR as a reference value, the relative risks for cardiovascular and respiratory hospital admission associated with extremely high DTR (11.6 °C) at cumulative lag 0-21 (21-day cumulative effects) were 1.206 (95% CI: 1.002-1.452) and 1.021 (95% CI: 0.856-1.218), respectively. The effects of extremely high DTR relative to a reference value did not significantly differ between males and females, as well as between young people (<65 years) and the elderly (≥65 years) for both cardiovascular and respiratory admission. When stratifying the effects by season, the effect of extremely high DTR in winter was greater than that in summer and rainy season. This study showed that short-term exposure to extremely high DTR was significantly associated with increased risk of hospital admissions for cardiovascular disease in Bangkok, especially during winter. Results from this study could provide important scientific evidence for policy decision making to protect populations from adverse health effects of DTR.

The changing climate-migration relationship in China, 1989-2011

A persistent concern about the social consequences of climate change is that large, vulnerable populations will be involuntarily displaced. Existing evidence suggests that changes in precipitation and temperature can increase migration in particular contexts, but the potential for this relationship to evolve over time alongside processes of adaptation and development has not been widely explored. To address this issue, we link longitudinal data from 20 thousand Chinese adults from 1989-2011 to external data on climate anomalies, and use this linked dataset to explore how climatic effects on internal migration have changed over time while controlling for potential spatial and temporal confounders. We find that temperature anomalies initially displaced permanent migrants at the beginning of our study period, but that this effect had reversed by the end of the study period. A parallel analysis of income shares suggests that the explanation might lie in climate vulnerability shifting from agricultural to non-agricultural livelihood activities. Taken together with evidence from previous case studies, our results open the door to a potential future in which development and in-situ adaptation allow climate-induced migration to decline over time, even as climate change unfolds.

An investigation of the prevalence of Giardia agilis in anuran amphibians from fourteen areas in China

Giardia agilis is a Giardia species which is morphological distinguishable for its very narrow and elongated trophozoite. Although there were a few studies about its morphology since its first report in 1882, none investigations about its prevalence have ever been reported to date. We investigated the prevalence of G. agilis in 25 anuran amphibian species from five provinces of China using both morphological and molecular methods. Of the 463 tested samples, 195 (42.1%) were positive. The 195 positive samples were from nine species, which are scatteredly distributed in four anuran amphibian families. The statistical prevalence among adults of different frog species showed no significant difference, and so did among tadpoles. Thus, G. agilis is probably able to infect all anuran amphibians without species-bias. More interestingly, the prevalence in the tadpoles is significantly higher than in their adults. The prevalence in Kaloula verrucosa tadpoles from the same area showed no significant differences between none-legged stage and two-legged stage, but the prevalence in these two developmental stages is significantly higher than in the four-legged stage. And the prevalence in four-legged stage is still much higher than in adults. A turning point of prevalence appeared in the period of tadpole tail degeneration. Moreover, all the positive samples were from the areas with relatively high altitude (more than 870 m). The fact that G. agilis tends to easily infect the frogs living in high altitude areas indicated it has evolved the ability to adapted the dramatic temperature change in poikilothermal animals. Therefore, G. agilis has evolved some special successful parasitism strategies for parasitizing the poikilothermal hosts with metamorphosis such as anuran amphibians.

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First reported on the prevalence of Giardia agilis.

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Giardia agilis might be able to infect all anuran amphibians.

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Giardia agilis evolved special ability to adapt the dramatic change of temperature.

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The prevalence in tadpoles was much higher than in adults.

Hourly associations between ambient temperature and emergency ambulance calls in one central Chinese city: Call for an immediate emergency plan

BACKGROUND

Most studies examining the short-term effects of temperature on health were based on the daily scale, few were at the hourly level. Revealing the relationship between unfavorable temperatures on an hourly basis and health is conducive to the development of more accurate extreme temperature early warning systems and reasonable dispatch of ambulances.

METHODS

Hourly data on temperature, air pollution (including PM_2.5, O₃, SO₂ and NO₂) and emergency ambulance calls (EACs) for all-cause, cardiovascular and respiratory diseases from January 16, 2014 to December 31, 2016 were obtained from Luoyang, China. A distributed lag non-linear model (DLNM) was used to assess the association between hourly temperature and ambulance calls after adjusting for potential confounding factors. The fractions of EACs attributable to non-optimum temperatures were also estimated.

RESULTS

Hourly temperature was associated with increased ambulance calls with a varying lag pattern. Extreme hot temperature (>32.1 °C) was positively associated with all-cause, cardiovascular diseases at lag 0-30 h and lag 0-9 h, while no significant effects were found for respiratory morbidity. Extreme cold temperature (<-2.5 °C) was positively associated with all-cause, cardiovascular and respiratory morbidity at lag 56-157 h, 50-145 h and 123-170 h. An overall EACs fraction of 6.84% [Backward estimate, 95% confidence interval (CI): 5.01%, 8.59%] could be attributed to non-optimum temperatures, and more contributions were caused by cold [Backward estimate: 6.06% (95% CI: 5.10%, 8.48%)] than by heat [Backward estimate: 0.79% (95% CI: 0.12%, 1.45%)].

CONCLUSIONS

Extreme hot temperature may lead to increased ambulance calls within a few hours, while extreme cold temperature may not increase ambulance calls until more than 2 days later. Effective measures, such as forming hourly temperature warning standards, optimizing ambulance services at extreme temperatures, etc., should be taken to reduce the unfavorable temperature - associated EACs burden.

Modification Effects of Temperature on the Ozone-Mortality Relationship: A Nationwide Multicounty Study in China

Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 μg/m³ increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.

Impact of temperature changes between neighboring days on COPD in a city in Northeast China

Sudden temperature changes between neighboring days (T_24h) have adverse effects on human health. In this study, we used a time series analysis to evaluate the impact of T_24h on the number of hospital admissions for chronic obstructive pulmonary disease (COPD) from 2009 to 2012 in Changchun (the capital of Northeast China's Jilin province). We performed the analysis in a generalized additive model (GAM), and the controlling factors included long-term trends, day of the week effect, and the selected weather elements. We divided the entire study group into two gender subgroups (males and females) and two age subgroups (aged < 65 years and aged ≥ 65 years). T_24h showed the greatest effect on the entire study group at lag 3 days. In particular, the greatest effect of T_24h on females (males) occurred at lag 1 day (lag 3 days); the greatest effect of T_24h on the aged ≥ 65 years (aged < 65 years) occurred at lag 1 day (lag 6 days). This indicates that temperature changes between neighboring days have a relatively more acute effect on the elderly and the females than on the younger people and the males. When T_24h is less than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 4 days during the warm season (1.025, 95% CI: 0.981, 1.069) and lag 3 days during the cold season (1.019, 95% CI: 0.988, 1.051). When T_24h is greater than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 6 days during the warm season (1.026, 95% CI: 0.977, 1.077) and lag 5 days during the cold season (1.021, 95% CI: 0.986, 1.057). The results of this study could be provided to local health authorities as scientific guidelines for controlling and preventing COPD in Changchun, China.

Associations of ambient temperature exposure during pregnancy with the risk of miscarriage and the modification effects of greenness in Guangdong, China

Miscarriage is one of the commonest complications of pregnancy. Although previous studies suggested that environmental factors were important causes of miscarriage, evidence is still inadequate. Here, we examined the association of maternal exposure to temperature with the risk of miscarriage and further assessed the modifying effects of surrounding residential greenness. A case-control study was conducted at a large hospital in Guangzhou, China. All participants' information was extracted from hospital records. An inverse distance weighted method was used to estimate the temperature exposure at each residential address, where the greenness was measured by Normalized Difference Vegetation Index (NDVI). A logistic regression model was applied to estimate the association of temperature exposure with the risk of miscarriage. A total of 2044 cases of miscarriage and 2285 controls were included in the present study. We observed a generally non-linear positive relationship between temperature exposure and the risk of miscarriage. More pronounced effects of high temperatures vs. low temperatures were found during the two months prior to hospitalization than in other periods. The odds ratio (OR) of 29.4 °C (95th centile) compared with 15 °C during the first month prior to hospitalization was 1.480 (95% CI: 1.021-2.145). Smaller effects of temperatures were seen on the risk of miscarriage among participants with moderately great surrounding greenness compared with those with less greenness. We concluded that maternal exposure to moderately high temperature during pregnancy may increase the risk of miscarriage, but the modifying effects of greenness on these associations need to be further tested in future studies.